OBJECTIVE: To evaluate the clinical efficacy of ultrasound-guided needle knife release with different pathways for carpal tunnel syndrome (CTS). METHODS: Sixty CTS patients were randomly divided into a transverse group and a longitudinal group, with 30 patients in each group. The transverse group received the needle knife release under ultrasound above and below the median nerve along the short axis, while the longitudinal group received the needle knife release under ultrasound above the median nerve along the long axis. The patients' visual analogue scale (VAS) scores, Levine scores, and median nerve cross-section area (CSA) were assessed before treatment, on the 7th, 14th, and 30th days after treatment. The median nerve conduction indexes (motor conduction: latency [Lat], amplitude[Amp], motor conduction velocity [MCV]; sensory conduction: Lat, Amp, sensory conduction velocity [SCV]) were evaluated before treatment and on the 30th day after treatment. RESULTS: Compared before treatment, the VAS scores, Levine scores, and median nerve CSA were reduced in both groups on the 7th, 14th, and 30th days after treatment (P<0.05); the transverse group showed lower VAS and Levine scores and smaller CSA than those in the longitudinal group (P<0.05). On the 30th day after treatment, motor and sensory Lat was reduced (P<0.05), motor and sensory Amp was increased (P<0.05), and MCV and SCV were faster (P<0.05) in both groups. The transverse group had shorter Lat, higher Amp, and faster MCV and SCV than those in the longitudinal group (P<0.05). CONCLUSION The ultrasound-guided needle knife release with transverse and longitudinal pathways could both effectively alleviate pain and improve median nerve conduction in CTS patients, with the transverse pathway showing superior efficacy to longitudinal pathway.
Humans ; Carpal Tunnel Syndrome/therapy* ; Female ; Middle Aged ; Male ; Adult ; Median Nerve/physiopathology* ; Acupuncture Therapy/instrumentation* ; Treatment Outcome ; Neural Conduction ; Aged ; Ultrasonography

OBJECTIVES: Non-small cell lung cancer (NSCLC) is associated with poor prognosis, with 30% of patients diagnosed at an advanced stage. Mutations in the EGFR and KRAS genes are important prognostic factors for NSCLC, and targeted therapies can significantly improve survival in these patients. Although tissue biopsy remains the gold standard for detecting gene mutations, it has limitations, including invasiveness, sampling errors due to tumor heterogeneity, and poor reproducibility. This study aims to develop machine learning models based on radiomic features to predict EGFR and KRAS gene mutation status in NSCLC patients, thereby providing a reference for precision oncology. METHODS: Imaging and mutation data from eligible NSCLC patients were obtained from the publicly available Lung-PET-CT-Dx dataset in The Cancer Imaging Archive (TCIA). A three-dimensional-convolutional neural network (3D-CNN) was used to extract imaging features from the regions of interest (ROI). The LightGBM algorithm was employed to build classification models for predicting EGFR and KRAS gene mutation status. Model performance was evaluated using 5-fold cross-validation, with receiver operator characteristic (ROC) curves, area under the curve (AUC), accuracy, sensitivity, and specificity used for validation. RESULTS: The models effectively predicted EGFR and KRAS mutations in NSCLC patients, achieving an AUC of 0.95 for EGFR mutations and 0.90 for KRAS. The models also demonstrated high accuracy (EGFR 89.66%; KRAS 87.10%), sensitivity (EGFR 93.33%; KRAS 87.50%), and specificity (EGFR 85.71%; KRAS 86.67%). CONCLUSIONS A radiogenomics-machine learning predictive model can serve as a non-invasive tool for anticipating EGFR and KRAS gene mutation status in NSCLC patients.
Humans ; Carcinoma, Non-Small-Cell Lung/diagnostic imaging* ; Lung Neoplasms/diagnostic imaging* ; Mutation ; Proto-Oncogene Proteins p21(ras)/genetics* ; ErbB Receptors/genetics* ; Machine Learning ; Positron Emission Tomography Computed Tomography ; Female ; Male ; Neural Networks, Computer ; Middle Aged ; Aged

Progressing stroke(PS)as a special type of ischemic stroke,accounts for approximately 10％to 40％of ischemic strokes.Compared with non-progressing stroke,PS has a higher mortality and disability rate.Large vessel disease is the most common cause of PS.However,due to the extended onset time,there is still considerable debate over the endovascular treatment of PS,and current treatment is primarily based on medication.This article provides a review of the current status of research on endovascular treatment for progressive stroke caused by large vessel disease,with the aim of offering a reference for clinical diagnosis,treatment,and related research.